Update app.py

app.py

@@ -2,22 +2,24 @@ import gradio as gr
 from transformers import GPT2LMHeadModel, GPT2Tokenizer
 import torch
 
-# Load model and tokenizer
-model_name = "openai-community/gpt2-large"
+# Load GPT-2 (community version) model and tokenizer
+model_name = "openai-community/gpt2"
 tokenizer = GPT2Tokenizer.from_pretrained(model_name)
 model = GPT2LMHeadModel.from_pretrained(model_name)
 
 # Set padding token (GPT-2 doesn't have one by default)
 tokenizer.pad_token = tokenizer.eos_token
-model.config.pad_token_id = model.config.eos_token_id
+model.config.pad_token_id = tokenizer.eos_token_id
 
 # Chat function
 def chat_with_gpt2(user_input):
+    # Tokenize and encode user input
     inputs = tokenizer.encode(user_input, return_tensors="pt", truncation=True, max_length=512)
-    
+
+    # Generate response
     outputs = model.generate(
         inputs,
-        max_length=250,  # shortened for performance
+        max_length=250,
         num_return_sequences=1,
         do_sample=True,
         temperature=0.7,
@@ -25,11 +27,12 @@ def chat_with_gpt2(user_input):
         top_p=0.95,
         pad_token_id=tokenizer.eos_token_id
     )
-    
+
+    # Decode and return the generated response
     response = tokenizer.decode(outputs[0], skip_special_tokens=True)
     return response[len(user_input):].strip()
 
-# Gradio UI
+# Gradio interface
 interface = gr.Interface(
     fn=chat_with_gpt2,
     inputs=gr.Textbox(lines=3, placeholder="Ask me about your trip..."),
@@ -38,4 +41,5 @@ interface = gr.Interface(
     description="Ask anything related to your travel or itinerary!"
 )
 
+# Launch the Gradio app
 interface.launch()